Phenomic Approaches and Tools for Phytopathologists
| Autor: | Xavier Sirault, Ivan Simko, José A. Jiménez-Berni |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0106 biological sciences
0301 basic medicine medicine.medical_specialty Genotype Genomics Plant Science Computational biology Phenome Biology 01 natural sciences Plant Physiological Phenomena 03 medical and health sciences Phenomics Optical imaging Image Processing Computer-Assisted medicine Plant Diseases business.industry Optical Imaging Phenotypic trait Plant Pathology Plants Magnetic Resonance Imaging Spectral imaging Biotechnology Phenotype 030104 developmental biology Thermography Host-Pathogen Interactions business Agronomy and Crop Science 010606 plant biology & botany |
| Zdroj: | Phytopathology®. 107:6-17 |
| ISSN: | 1943-7684 0031-949X |
| DOI: | 10.1094/phyto-02-16-0082-rvw |
| Popis: | Plant phenomics approaches aim to measure traits such as growth, performance, and composition of plants using a suite of noninvasive technologies. The goal is to link phenotypic traits to the genetic information for particular genotypes, thus creating the bridge between the phenome and genome. Application of sensing technologies for detecting specific phenotypic reactions occurring during plant−pathogen interaction offers new opportunities for elucidating the physiological mechanisms that link pathogen infection and disease symptoms in the host, and also provides a faster approach in the selection of genetic material that is resistant to specific pathogens or strains. Appropriate phenomics methods and tools may also allow presymptomatic detection of disease-related changes in plants or to identify changes that are not visually apparent. This review focuses on the use of sensor-based phenomics tools in plant pathology such as those related to digital imaging, chlorophyll fluorescence imaging, spectral imaging, and thermal imaging. A brief introduction is provided for less used approaches like magnetic resonance, soft x-ray imaging, ultrasound, and detection of volatile compounds. We hope that this concise review will stimulate further development and use of tools for automatic, nondestructive, and high-throughput phenotyping of plant−pathogen interaction. |
| Databáze: | OpenAIRE |
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